Measurements of extracellular electric field potentials are widely used in clinical diagnostics and across a broad range of research contexts in cognitive psychology, neurophysiology, and systems neuroscience. Different forms of electroencephalographic (EEG) oscillations and event-related potentials are indicative of various brain states that are associated with distinct behaviors, modes of cognition and disease. In most cases, however, the physiological origins, functional importance and computational roles of electrical potential dynamics and their intracellular correlates remain unclear.
Extracellular field potentials generally reflect the combined dynamics of multiple cell types and electrophysiological mechanisms across a broad range of length scales. This mechanistic complexity has precluded general cell biological interpretations of both normal and pathological electric field oscillations, especially in deep-brain regions. Laminar brain structures such as the mammalian cortex and hippocampus permit charge source density analyses that have allowed some empirical dissections of the electrical sources and sinks in different tissue layers. These analyses are, however, generally uninformative in non-laminar brain structures such as the striatum that contain intermingled, heterogeneous cell types.
What is needed in the art is a tool capable of measuring biological parameters, such as trans-membrane potential dynamics, in a cell-type specific manner, in actively behaving animals. Electrophysiological approaches for measuring intracellular voltage dynamics are usually limited to recordings in single cells and are also nearly prohibitive to perform in a manner that targets specific cell types in behaving animals, especially in sub-cortical brain areas. By comparison, optical techniques for recording the dynamics of large populations of specific neuron-types can work well in behaving animals, via targeted expression of fluorescent protein indicators of intracellular Ca′ concentration. However, intracellular [Ca2+] is an indirect correlate of membrane depolarization, is a poor proxy of spiking activity in many cell types, tracks neither subthreshold, inhibitory, nor oscillatory neural activity well, and does not report fast dynamics on timescales finer than about 25 to 50 milliseconds. These limitations preclude the use of Ca2+ indicators as a general means of tracking large-scale brain oscillatory dynamics in live mammals.
In contrast to these established approaches, genetically encoded fluorescent indicators of membrane voltage directly report both sub-threshold and inhibitory trans-membrane voltage activity. Such indicators therefore provide a possible means of tracking neural membrane potentials in a cell-type specific way in behaving animals. Several prior studies have used either synthetic or genetically encoded fluorescent voltage indicators to monitor sensory evoked potentials in the rodent neocortex. Other optical studies have tracked neocortical voltage oscillations in rodents under or in recovery from anesthesia. However, even the most sensitive existing protein voltage indicators offer modest signaling dynamic ranges; that is, about 1% fluorescence changes (ΔF/F) per 10 mV voltage change in vitro and about 0.5% when averaged across a population in vivo. These amplitudes are comparable to the dynamic ranges of hemodynamic and brain motion artifacts that arise in vivo: about 1% optical fluctuations across 0.1-15 Hz bandwidth. Even in anesthetized animals, sufficient elevation of genetically-encoded voltage signals above physiological noise sources has thus required a combination of single trial averaging and the use of less-sensitive, two-color FRET voltage sensors to reduce physiological artifacts.
An even more persistent obstacle to the use of both genetically-encoded and synthetic fluorescent voltage sensors is recording noise introduced by photon-shot noise. That is, the intrinsic fluctuations in optical experiments introduced by the randomness of photon emission and detection processes. The relative variance of shot noise in optical recordings is inversely proportional to the light intensity. Photobleaching rates depend exponentially on illumination power, which has generally limited recording lengths to tens of seconds to several minutes. No prior optical system has had the detection sensitivity needed to overcome the shot noise and physiological artifacts that are unavoidably present in optical recordings in unrestrained animals and to monitor voltage oscillations in freely behaving mammals.